Conventional caches operate by caching the results of previous calls so that future calls do not necessarily require as much processing, at least to the extent that such processing was performed in connection with one of the cached earlier calls. In some situations, the cache-controlling software may cause expiration of cache entries based on a policy relating to one or more characteristics (for example, data size, data age, data usage). Some conventional caches are also enhanced with pre-loading of entries before the initial request has entered the system. This pre-loading is normally completed using at least one of the following: (i) a static list defined by the administrator of the system; and/or (ii) potentially based on the previous content of the cache. Currently conventional pre-loading of the cache using previous content usually reviews the content of the cache before a shutdown and replicates this within the new system.
For purposes of this document, analytics is defined as the discovery, by software, of meaningful patterns in machine readable data. Typically, analytics relies on knowledge from disciplines such as statistics, computer programming and operations research to quantify performance and thereby discover patterns. Analytics sometimes uses “data visualization” to communicate insight. It is known to apply analytics to business data, to describe, predict, and improve business performance. Specifically, arenas within analytics include enterprise decision management, retail analytics, store assortment and SKU optimization, marketing optimization and marketing mix analytics, web analytics, sales force sizing and optimization, price and promotion modeling, predictive science, credit risk analysis, and/or fraud analytics. Typically, analytics is not so much concerned with individual analyses or analysis steps, but with the entire methodology.